Lauren E. Margulieux

1.7k citations
56 papers · 1.0k indexed · h-index 17

Lauren E. Margulieux

51 papers receiving 978 citations

Peers

Lauren E. Margulieux
Comparison fields: 5 of 65
  • Computer Science Applications 748
  • Developmental and Educational Psychology 497
  • Software 40
  • Media Technology 82
  • Information Systems 206
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Citations per field
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Citations per year

Countries citing papers authored by Lauren E. Margulieux

Since Specialization
Citations

This map shows the geographic impact of Lauren E. Margulieux's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lauren E. Margulieux with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lauren E. Margulieux more than expected).

Fields of papers citing papers by Lauren E. Margulieux

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lauren E. Margulieux. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lauren E. Margulieux. The network helps show where Lauren E. Margulieux may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Lauren E. Margulieux, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Lauren E. Margulieux Line = papers co-authored together Lauren E. Margulieux links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20250
4 20242
5 202418
6 20242
7 20241
8 20232
9 20232
10 202265
11 202216
12 202218
13
Conclusions From the Validation of a Vignette-Based Instrument to Measure Maker Mindsets.
20201
14
Measuring Maker Mindset: Establishing Content Validity with Card Sorting.
20182
15
Training learners to self-explain: Designing instructions and examples to improve problem solving
20163
16
Using subgoal learning and self-explanation to improve programming education
20165
17 201631
18 20156
19
Improving Programming Instruction with Subgoal Labeled Instructional Text
20145
20
Subgoal Labeled Worked Examples Improve K-12 Teacher Performance in Computer Programming Training
20136

About Lauren E. Margulieux

Lauren E. Margulieux is a scholar working on Computer Science Applications, Developmental and Educational Psychology, Experimental and Cognitive Psychology, Gender Studies and Media Technology, having authored 56 papers that have together received 1.0k indexed citations. Recurring topics across this work include Teaching and Learning Programming (37 papers), Innovative Teaching and Learning Methods (27 papers), Online Learning and Analytics (26 papers), Visual and Cognitive Learning Processes (8 papers), Educational Games and Gamification (8 papers), Gender and Technology in Education (6 papers), Experimental Learning in Engineering (4 papers) and Intelligent Tutoring Systems and Adaptive Learning (4 papers). The work is most often cited by research in Computer Science Applications (748 citations), Developmental and Educational Psychology (497 citations), Software (40 citations), Media Technology (82 citations) and Information Systems (206 citations). Lauren E. Margulieux has collaborated with scholars based in United States, New Zealand and Ireland. Frequent co-authors include Richard Catrambone, Mark Guzdial, Briana B. Morrison, Adrienne Decker, Barbara Ericson, Jochen Rick, Paul Denny, Brett A. Becker, James Prather and Dastyni Loksa. Their work appears in journals such as Computer Science Education, ACM Transactions on Computing Education, Cognitive Science, Communications of the ACM and Computing in Science & Engineering.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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